An MCMC Sampler Using the t-Walk Algorithm R package Rtwalk version 2.0.2 Implements the t-walk algorithm, a general-purpose, self-adjusting Markov Chain Monte Carlo (MCMC) sampler for continuous distributions as described by Christen & Fox (2010) <doi:10.1214/10-BA603>. The t-walk requires no tuning and is robust for a wide range of target distributions, including high-dimensional and multimodal problems. This implementation includes an option for running multiple chains in parallel to accelerate sampling and facilitate convergence diagnostics. Software Imports: parallel, stats, utils, graphics, grDevices, coda Suggests: testthat (>= 3.0.0), covr, mvtnorm, devtools, roxygen2, knitr, rmarkdown, ellipse Rodrigo Fonseca Villa <rodrigo03.villa@gmail.com> Comprehensive R Archive Network (CRAN) Rodrigo Fonseca Villa [aut, cre] (ORCID: <https://orcid.org/0009-0005-2938-2270>) GPL-3 2026-07-30 application/tgz https://CRAN.R-project.org/package=Rtwalk doi:10.32614/CRAN.package.Rtwalk